Industries

Christopher J. Malloy

Christopher Malloy is a Professor in the Finance Unit at Harvard Business School, and a Faculty Research Fellow at the National Bureau of Economic Research. Prior to joining HBS in 2007, Professor Malloy was an Assistant Professor in the Finance Department at London Business School, where he was on faculty from 2003-2007.

Professor Malloy currently teaches the second semester investment strategies and stock pitching courses at HBS, and has previously taught courses in behavioral finance, corporate finance, and equity investment management. His research focuses on behavioral finance, asset pricing, investments and portfolio choice, labor economics, and empirical corporate finance. His research has appeared in the Journal of Political Economy, the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies, and has been described in The Financial Times, The Wall Street Journal, The New York Times, and various other media outlets.

Professor Malloy received a PhD in Finance and an MBA from The University of Chicago Graduate School of Business, and a BA in Economics from Yale University. Before beginning his doctoral studies, he worked at the Board of Governors of the Federal Reserve System in Washington, DC in the Monetary and Financial Studies Section.

We demonstrate that simply by using the ethnic makeup surrounding a firm’s location, we can predict, on average, which trade links are valuable for firms. Using customs and port authority data on the international shipments of all U.S. publicly traded firms, we show that firms are significantly more likely to trade with countries that have a large resident population near their firm headquarters. We use the formation of World War II Japanese Internment Camps to isolate exogenous shocks to local ethnic populations and identify a causal link between local networks and firm trade. We also show that firms are more likely to acquire target firms, and report increased segment sales, in countries to which they are connected. Firms that exploit their local networks also see significant increases in future sales growth and profitability. In sum, our results document a surprisingly large impact of immigrants’ role as economic conduits for firms in their new countries.

We demonstrate that personal connections amongst U.S. politicians have a significant impact on Senate voting behavior. Networks based on alumni connections between politicians are consistent predictors of voting behavior. We estimate sharp measures that control for common characteristics of the network, as well as heterogeneous impacts of a common network characteristic across votes. We find that the effect of alumni networks is close to 60% as large as the effect of state-level considerations. The network effects we identify are stronger for more tightly linked networks, and at times when votes are most valuable. We show that politicians use school ties as a mechanism to engage in vote trading ("logrolling"), and that alumni networks help facilitate the procurement of discretionary earmarks.

We demonstrate that legislation has a simple, yet previously undetected impact on stock prices. Exploiting the voting record of legislators whose constituents are the affected industries, we show that the votes of these "interested" legislators capture important information seemingly ignored by the market. A long-short portfolio based on these legislators' views earns abnormal returns of over 90 basis points per month following the passage of legislation. Industries that we classify as beneficiaries of legislation experience significantly more positive earnings surprises and positive analyst revisions in the months following passage of the bill, as well as significantly higher future sales and profitability. We show that the more complex the legislation, the more difficulty the market has in assessing the impact of these bills; further, the more concentrated the legislator's interest in the industry, the more informative are her votes for future returns.

We demonstrate that a firm's ability to innovate is predictable, persistent, and relatively simple to compute, and yet the stock market ignores the implications of past successes when valuing future innovation. We show that two firms that invest the exact same in research and development (R&D) can have quite divergent, but predictably divergent, future paths. Our approach is based on the simple premise that while future outcomes associated with R&D investment are uncertain, the past track records of firms may give insight into their potential for future success. We show that a long-short portfolio strategy that takes advantage of the information in past track records earns abnormal returns of roughly 11% per year. Importantly, these past track records also predict divergent future real outcomes in patents, patent citations, and new product innovations.

This paper employs a new empirical approach for identifying the impact of government spending on the private sector. Our key innovation is to use changes in congressional committee chairmanship as a source of exogenous variation in state-level federal expenditures. In doing so, we show that fiscal spending shocks appear to significantly dampen corporate sector investment and employment activity. This retrenchment follows both Senate and House committee chair changes, occurs in large and small firms and within large and small states, and is most pronounced among geographically concentrated firms. The effects are economically meaningful and the mechanism-entirely distinct from the more traditional interest rate and tax channels-suggests new considerations in assessing the impact of government spending on private sector economic activity.

Using a simple empirical strategy, we decode the information in insider trading. Exploiting the fact that insiders trade for a variety of reasons, we show that there is predictable, identifiable "routine" insider trading that is not informative for the future of firms. Stripping away the trades of routine insiders leaves a set of information-rich trades by "opportunistic" insiders that contain all the predictive power in the insider trading universe. A portfolio strategy that focuses solely on opportunistic traders yields value-weighted abnormal returns of 82 basis points per month, while the abnormal returns associated with routine traders are essentially zero. Further, opportunistic insiders predict future firm-specific news, as well as announcement returns around future analyst forecasts, management forecasts, and earnings announcements, while routine traders do not. The most informed opportunistic traders are local non-senior insiders, who come from geographically concentrated, poorly governed firms. Lastly, opportunistic traders are significantly more likely to have SEC enforcement action taken against them and reduce their trading following waves of SEC insider trading enforcement.

We provide evidence that firms appoint independent directors who are overly sympathetic to management, while still technically independent according to regulatory definitions. We explore a subset of independent directors for whom we have detailed, micro-level data on their views regarding the firm prior to being appointed to the board: sell-side analysts who are subsequently appointed to the boards of companies they previously covered. We find that boards appoint overly optimistic analysts who are also poor relative performers. The magnitude of the optimistic bias is large: 82.0% of appointed recommendations are strong-buy/buy recommendations, compared to 56.9% for all other analyst recommendations. We also show that appointed analysts' optimism is stronger at precisely those times when firms' benefits are larger. Lastly, we find that appointing firms are more likely to have management on the board nominating committee, appear to be poorly governed, and increase earnings management and CEO compensation following these board appointments.

We study the impact of social networks on agents' ability to gather superior information about firms. Exploiting novel data on the educational backgrounds of sell-side equity analysts and senior officers of firms, we test the hypothesis that analysts' school ties to senior officers impart comparative information advantages in the production of analyst research. We find evidence that analysts outperform on their stock recommendations when they have an educational link to the company. A simple portfolio strategy of going long the buy recommendations with school ties and going short buy recommendations without ties earns returns of 6.60% per year. We test whether Regulation FD, targeted at impeding selective disclosure, constrained the use of direct access to senior management. We find a large effect: pre-Reg FD the return premium from school ties was 9.36% per year, while post-Reg FD the return premium was nearly zero and insignificant. In contrast, in an environment that did not change selective disclosure regulation (the U.K.), the analyst school-tie premium has remained large and significant over the entire sample period.

We provide new evidence on the success of long-run risks in asset pricing by focusing on the risks borne by stockholders. Exploiting micro-level household consumption data, we show that long-run stockholder consumption risk better captures cross-sectional variation in average asset returns than aggregate or non-stockholder consumption risk, and provides more plausible economic magnitudes. We find that risk aversion estimates around 10 can match observed risk premia for the wealthiest stockholders across sets of test assets that include the 25 Fama and French size and value portfolios, the market portfolio, bond portfolios, and the entire cross-section of stocks.

We document widespread ex post changes to the historical contents of the I/B/E/S analyst stock recommendations database. Across a sequence of seven downloads of the entire I/B/E/S recommendations database, obtained between 2000 and 2007, we find that between 6,594 (1.6%) and 97,579 (21.7%) of matched observations are different from one download to the next. The changes, which include alterations of recommendation levels, additions and deletions of records, and removal of analyst names, are non-random in nature: They cluster by analyst reputation, brokerage firm size and status, and recommendation boldness. The changes have a large and significant impact on the classification of trading signals and back-tests of three stylized facts: The profitability of trading signals, the profitability of changes in consensus recommendations, and persistence in individual analyst stock-picking ability.

This paper uses social networks to identify information transfer in security markets. We focus on connections between mutual fund managers and corporate board members via shared education networks. We find that portfolio managers place larger bets on firms they are connected to through their network, and perform significantly better on these holdings relative to their non-connected holdings. A replicating portfolio of connected stocks outperforms a replicating portfolio of non-connected stocks by up to 7.8% per year. Returns are concentrated around corporate news announcements, consistent with mutual fund managers gaining an informational advantage through the education networks. Our results suggest that social networks may be an important mechanism for information flow into asset prices.

Using proprietary data on stock loan fees and quantities from a large institutional investor, we examine the link between the shorting market and stock prices. Employing a unique identification strategy, we isolate shifts in the supply and demand for shorting. We find that shorting demand is an important predictor of future stock returns: An increase in shorting demand leads to negative abnormal returns of 2.98% in the following month. Second, we show that our results are stronger in environments with less public information flow, suggesting that the shorting market is an important mechanism for private information revelation.

I provide evidence that geographically proximate analysts are more accurate than other analysts. Stock returns immediately surrounding forecast revisions suggest that local analysts impact prices more than other analysts. These effects are strongest for firms located in small cities and remote areas. Collectively these results suggest that geographically proximate analysts possess an information advantage over other analysts, and that this advantage translates into better performance. The well-documented underwriter affiliation bias in stock recommendations is concentrated among distant affiliated analysts; recommendations by local affiliated analysts are unbiased. This finding reveals a geographic component to the agency problems in the industry.

We provide evidence that stocks with higher dispersion in analysts' earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks, and stocks that have performed poorly over the past year. Interpreting dispersion in analysts' forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts' forecasts proxies for risk.

We explore a subtle but important mechanism through which firms can control information flow to the markets. We find that firms that “cast” their conference calls by disproportionately calling on bullish analysts tend to underperform in the future. Firms that call on more favorable analysts experience more negative future earnings surprises and more future earnings restatements. A long-short portfolio that exploits this differential firm behavior earns abnormal returns of up to 149 basis points per month, or almost 18 percent per year. We find similar evidence in an international sample of earnings call transcripts from the UK, Canada, France, and Japan. Firms with higher discretionary accruals, firms that barely meet/exceed earnings expectations, and firms (and their executives) that are about to issue equity, sell shares, and exercise options, are all significantly more likely to cast their earnings calls.

Much like states that rely on government spending, certain firms rely on the government for a substantial share of their revenues. Exploiting the statutory requirement that forces firms to list the identities of their major customers, we identify and examine the set of firms whose major customers are listed as government entities. We employ an identification strategy that exploits government contract bid protests in order to identify the causal impact of government sales on future firm outcomes, and find that government-linked firms invest less in physical and intellectual capital, and have lower future sales growth.

In the summer of 2008, AQR Capital Management was considering the launch of a new hedge fund strategy. The proposed DELTA portfolio would offer investors exposure to a basket of nine major hedge fund strategies. The DELTA strategy would be innovative in two ways. First, in terms of its structure, AQR would implement these underlying strategies using a well-defined investment process, with the goal being to deliver exposure to a well-diversified portfolio of hedge fund strategies. Second, in terms of its fees, the new DELTA strategy would charge investors relatively lower fees: 1% management fees plus 10% of performance over a cash hurdle (or, alternatively, a management fee of 2% only). This fee structure was low relative to the industry, where 2% management fees plus 20% of performance, often with no hurdle, was standard.

This case examines Dimensional Fund Advisors (DFA)'s decision to enter the retirement market with their new "Dimensional Managed DC" product, a complete retirement solution that aimed to provide investors with what they really wanted: the same standard of living in retirement that they had while working. The case considers the challenges of entering the fiercely competitive retirement market, introduces students to the large literature on the behavioral biases of individual investors, and asks students to evaluate an innovative new financial product designed to automate the process of retirement investing.

AQR is a hedge fund based in Greenwich, Connecticut, that is considering offering a wholly new line of product to retail investors, namely the ability to invest in the price phenomenon known as momentum. There is a large body of empirical evidence supporting momentum across many different asset classes and countries. However, up until this point, momentum was a strategy employed nearly exclusively by hedge funds, and thus not an available investment strategy to most individual investors. This case highlights the difficulties in implementing this "mutual fund-itizing" of a hedge fund product, along with the challenges that the open-end and regulatory features that a mutual fund poses to many successful strategies implemented in other contexts. In addition, it gives students the ability to calculate and interpret various horizons of correlations between many popular investment strategies using long time-series data and then thinking about the potential complementarities of strategies from a portfolio construction context.

This is a (B) case for AQR's Momentum Funds. It follows the first year of performance of the funds after launching, and gives students a critical inflection point for analyzing the nascent stages of a new product launch and the potential path dependence of the product depending on initial returns. It allows students to wrestle with the way forward given these conditions, and how (if at all) it changes their views, pitch, and perspective on the strategy, and traditional long-short strategies more generally.

Miracle Life is a firm with a unique setup and organizational structure. Specifically, it is a network marketing firm, also known as multi-level marketing (MLM) firm, which utilizes a large distributor base and depends on this individual distributor base to sell its products, giving explicit incentives for these individual distributors to both sell its products and sign up other distributors. The case gives students the opportunity to take the basic framework of Discounted Cash Flow (DCF) Analysis and apply it to two unique perspectives of an identical problem. The students will then use this DCF approach to rationalize observed stock prices, connecting the two, and further reconcile how a company's future plan for growth, and the plausibility of this plan, has implications jointly for DCF and stock prices.

PlanetTran is an environmentally-friendly car service that utilizes a fleet of hybrid cars in providing livery service to corporations and individuals. The founder, Seth Riney, is evaluating outside funding options in order to expand the company, and has met several local venture capital (VC) firms, Riney must decide if the dilution he would have to undergo in order to accept a substantial capital investment was worth the added upside to the company that both he and the VCs envisioned.

Tottenham Hotspur Football Club is a publicly-owned professional soccer team based in London, England. The club's chairman, Daniel Levy, is contemplating a significant investment in physical assets, including the development of a new stadium as well as the acquisition of a new player. The team must decide if the expected cash flows associated with adding the stadium, the player, or both, warrant the considerable required investments in these assets.